Rapid and reliable identification of insects is important in many contexts, from the detection of disease vectors and invasive species to the sorting of material from biodiversity inventories. Because of the shortage of adequate expertise, there has long been an interest in developing automated systems for this task. Previous attempts have been based on laborious and complex handcrafted extraction of image features, but in recent years it has been shown that sophisticated convolutional neural networks (CNNs) can learn to extract relevant features automatically, without human intervention. Unfortunately, reaching expert-level accuracy in CNN identifications requires substantial computational power and huge training data sets, which are often not available for taxonomic tasks. This can be addressed using feature transfer: a CNN that has been pretrained on a generic image classification task is exposed to the taxonomic images of interest, and information about its perception of those images is used in training a simpler, dedicated identification system. Here, we develop an effective method of CNN feature transfer, which achieves expert-level accuracy in taxonomic identification of insects with training sets of 100 images or less per category, depending on the nature of data set. Specifically, we extract rich representations of intermediate to high-level image features from the CNN architecture VGG16 pretrained on the ImageNet data set. This information is submitted to a linear support vector machine classifier, which is trained on the target problem. We tested the performance of our approach on two types of challenging taxonomic tasks: 1) identifying insects to higher groups when they are likely to belong to subgroups that have not been seen previously and 2) identifying visually similar species that are difficult to separate even for experts. For the first task, our approach reached \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$CDATA[$CDATA[$>$$\end{document}92% accuracy on one data set (884 face images of 11 families of Diptera, all specimens representing unique species), and \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$CDATA[$CDATA[$>$$\end{document}96% accuracy on another (2936 dorsal habitus images of 14 families of Coleoptera, over 90% of specimens belonging to unique species). For the second task, our approach outperformed a leading taxonomic expert on one data set (339 images of three species of the Coleoptera genus Oxythyrea; 97% accuracy), and both humans and traditional automated identification systems on another data set (3845 images of nine species of Plecoptera larvae; 98.6 % accuracy). Reanalyzing several biological imag...

Cydistinae are a rare monogeneric beetle lineage from Asia with a convoluted history of classification, historically placed in various groups within the series Elateriformia. However, their position has never been rigorously tested. To resolve this long-standing puzzle, we are the first to present sequences of two nuclear and two mitochondrial markers for four species of Cydistinae to determine their phylogenetic position. We included these sequences in two rounds of analyses: one including a broad Elateriformia dataset to test placement at the superfamily/family level, and a second, including a richer, targeted sampling of presumed close relatives. Our results strongly support Cydistinae as sister to Phengodidae in a clade with Rhagophthalmidae. Based on our molecular phylogenetic results and examination of morphological characters, we hereby transfer the formerly unplaced Cydistinae into Phengodidae and provide diagnoses for the newly circumscribed Phengodidae, Cydistinae and Cydistus. Since both Phengodidae and Rhagophthalmidae have bioluminescent larvae and strongly neotenic females, similar features can be hypothesized for Cydistinae. Additionally, Cydistus minor is transferred to the new genus Microcydistus.

Senodoniini is a small lineage of click beetles currently comprising 21 species in two genera, distributed in the Himalayas and East and Southeast Asia. The definition and limits of this group have changed considerably during its history. Recent authors treat Senodoniini as a tribe within Dendrometrinae, usually close to Dimini, but this placement has never been rigorously tested. Here, we shed new light on the systematic position and limits of Senodoniini by performing a combined phylogenetic analysis of two nuclear and two mitochondrial molecular markers. Our results recovered Senodoniini not monophyletic, and placed them into the Lissominae complex, where they formed a clade with Austrelater Calder & Lawrence (Protelaterini). Molecular phylogeny is in agreement with the adult morphology. Additionally, we examined the morphology of a monotypic genus Rostricephalus Fleutiaux from Southeast Asia, which was previously classified in various Elateridae groups including Senodoniini, and its position was always uncertain. This genus shares morphological characters with Protelaterini. We provide morphological redescriptions as well as the figures of main diagnostic characters for Senodonia Laporte, Sossor Candèze, and Rostricephalus. Based on our results, we place these genera to Lissominae: Protelaterini, and hence synonymize Senodoniini Schenkling with Protelaterini Schwarz.

The genus Oxythyrea Mulsant, 1842 comprises ten currently recognized species. So far, larval descriptions for only three species are available. Here, we present comprehensive descriptions of third instar larval morphology for the six previously unstudied Oxythyrea species along with detailed re-descriptions of larval morphology for the previously described species. All descriptions are supplemented by photographs and line art drawings of the morphological structures. This work also contains a key to third instar larvae of the genus Oxythyrea as well as observations from collecting sites with focus on biological characteristics of all covered species including pictures of biotopes and host plants for adults. In addition, notes on the breeding circumstances for species are provided.